Arthritis & Rheumatology · 2024 · 10 citations · 19 references
Life SciencesCell BiologyImmunologyAutoimmunityInflammationRheumatologyInflammatory ArthritisInflammatory ProcessesRheumatoid ArthritisSingle-cell Rna Sequencing AnalysisSingle-cell TranscriptomicsSynovial InflammationCd8 Positive T CellsMemory T Cell SubsetsSingle-cell Rna SequencingSynovial Fluid Cell AnalysisSynovial Fluid CompositionT Cell Receptor SequencingT-cell Receptor Gene Sequencing
OBJECTIVE: Synovial fluid (SF)-derived T cells are frequently studied as a proxy for investigating the synovial tissue (ST) T cell infiltrate in inflammatory arthritis. However, because ST is the primary site of inflammatory activity, there is debate as to whether SF provides a true reflection of the ST T cell population. METHODS: In this study, we used single-cell RNA sequencing paired with single-cell T cell receptor (TCR) sequencing to directly compare memory T cells from paired samples of SF and ST from six patients with inflammatory arthritis to investigate their similarity in terms of TCR repertoire and T cell subset composition. RESULTS: The TCR repertoires of SF and ST T cells were strikingly similar, particularly for CD8+ T cells. A median of 49% of the total CD8+ TCR repertoire in SF was shared with ST, compared with 20% shared with blood. Similarly, 47% of the ST CD8+ TCR repertoire was shared with SF compared to 25% with blood. Furthermore, once the effect of collagenase digestion on gene expression by ST T cells had been accounted for, the frequencies of specific CD8+ and CD4+ T cell subsets were, in general, similar in SF and ST and were distinct from blood. CONCLUSION: Our results suggest that T cells migrate and equilibrate between the SF and ST and maintain similar phenotypes in both sites. We conclude that SF is an appropriate proxy for investigating the T cell infiltrate in inflamed synovium, particularly in terms of investigating the TCR repertoire.
19
Comprehensive Integration of Single-Cell Data
Tim Stuart, Andrew Butler, Paul Hoffman et al. · Cell · 2019 · 16.9K citations · Full text
NCBI GEO: archive for functional genomics data sets—update
Tanya Barrett, Stephen E. Wilhite, Pierre Ledoux et al. · Nucleic Acids Research · 2012 · 10.8K citations · Full text
Fast, sensitive and accurate integration of single-cell data with Harmony
Ilya Korsunsky, Nghia Millard, Jean Fan et al. · Nature Methods · 2019 · 10.5K citations · Full text